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Research on Energy-Saving Efficiency and Influencing Factors of Green and Low-Carbon Enterprises Based on Three-Stage DEA and Tobit Models

Author

Listed:
  • Fenfang Xu

    (School of Resource and Security Engineering, Wuhan Institute of Technology, Wuhan 430074, China)

  • Teng Shao

    (Domestic Cooperation Office, University of International Business and Economics, Beijing 100029, China)

  • Ruili Hu

    (Department of Security, University of International Business and Economics, Beijing 100029, China)

  • Minbo Zhang

    (School of Resource and Security Engineering, Wuhan Institute of Technology, Wuhan 430074, China)

Abstract

Implementing the “dual-carbon” objective has profoundly affected China’s businesses, prompting a continuous process of transformation and innovation. Green, low-carbon transformation, upgrading, and sustainable development have emerged as the means to achieve high-quality company growth, with firms playing a crucial role in achieving the “dual-carbon” target. By prioritizing firms’ green, low-carbon, and sustainable growth, not only can their economic efficiency be improved, but it also serves as a vital measure to advance high-quality development. To achieve this objective, it is crucial to analyze the elements that impact the energy-saving effectiveness of businesses to develop optimization tactics that can enhance their competitiveness. This study combines the three-stage Data Envelopment Analysis (DEA) and the Tobit model to assess the energy-saving efficiency of green and low-carbon firms from 2018 to 2022. The analysis focuses on selected samples from various areas and industries. The study investigates the relationship between energy-saving effectiveness and different regional and industrial parameters, considering the distinct attributes of each firm and the key elements that influence its energy-saving performance. The findings indicate that green, low-carbon firms typically demonstrate suboptimal energy-saving efficiency but have considerable room for improvement. Upon considering environmental concerns, it becomes clear that the primary limitation on energy-saving performance is the lower efficiency of the enterprise scale. The energy-saving efficiency of green, low-carbon firms varies significantly across different regions and industries. On average, northern firms in the energy-saving and carbon reduction industry, as well as the resource recycling industry, have higher energy-saving efficiency compared to southern enterprises. In contrast, the environmental protection industry in southern firms demonstrates a better average energy-saving efficiency compared to their northern counterparts. Employee quality, policy support, and automation are key factors that greatly enhance the energy-saving efficiency of firms in both regions. Enterprise size has a beneficial impact on the energy-saving efficiency of southern firms but a negative impact on northern enterprises. Moreover, the industry and financial structures exert a detrimental influence on enhancing the energy-saving efficiency of green and low-carbon firms. Thus, in order to improve the energy-saving effectiveness of businesses, it is essential to utilize the elements that have a positive influence on energy-saving performance and reduce the impact of those that have negative impacts. This strategy will enhance the energy-saving efficiency of businesses and promote the development of an environmentally friendly and low-carbon society.

Suggested Citation

  • Fenfang Xu & Teng Shao & Ruili Hu & Minbo Zhang, 2024. "Research on Energy-Saving Efficiency and Influencing Factors of Green and Low-Carbon Enterprises Based on Three-Stage DEA and Tobit Models," Sustainability, MDPI, vol. 16(17), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7373-:d:1465000
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    References listed on IDEAS

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    1. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
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